Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi
Daris Fauzaan
Universitas Singaperbangsa Karawang
Religion Humanities Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Komparasi Algoritma Regresi Linear Klasik Dan Bayes Dalam Mengestimasi Lahan Tempat Pembuangan Sampah Daris Fauzaan; Betha Nurina Sari; Iqbal Maulana
JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi Vol 21 No 2 (2022): September 2022
Publisher : LP2M STAI Miftahul 'Ula (STAIM) Nganjuk

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/lentera.v21i2.787

Abstract

The development of the current population is increasing, over time the production of waste also participates in the increase. In their daily life, Indonesian people are not spared in producing waste due to economic activity factors such as consumption and distribution. In a long time, the production of this waste will increase and result in the reduction of land for final waste disposal (TPA) and can result in overload. Therefore, in this study, we will estimate the availability of land in the Jalupang TPA using the classical simple linear regression and Bayesian methods. For supporting data using population data and waste volume data in the previous year. In this study, we will use Mean Absolute Error (MAE) and Mean Percentage Error (MAPE) to evaluate the performance of classical simple linear regression and Bayesian methods in predicting the amount of waste volume. The results obtained are predictions of the volume of waste in 2030 using the classical simple linear regression method as much as 3302506.262 tons, and by using the Bayes simple linear regression method as many as 3301478.933 tons. As for the Jalupang TPA land that must be available in 2030, it is 39,303 ha. The results of the evaluation using the MAE value of the classical method 3739.425148 and the Bayes method 3739.063339 and the MAPE value of the classical method is 1.142425016% and the Bayes method is 1.142415877%.
Co-Authors Iqbal Maulana